In this paper we investigate a mesh-modeling approach for multi-modality image reconstruction. In the proposed approach a mesh model uses information obtained from an anatomical MR image to aid in reconstruction of PET images. The aim is to improve spatial resolution and quantitative accuracy of the PET image by using anatomical boundary information from the MR image. The mesh approach accompli...

We developed a maximum a posterior (MAP) reconstruction method for positron emission tomography (PET) image reconstruction incorporating magnetic resonance (MR) image information, with the joint entropy between the PET and MR image features serving as the regularization constraint. A non-parametric method was used to estimate the joint probability density of the PET and MR images. Using realist...

Medical images analysis is becoming increasingly important in clinical applications. One of the active resarch areas in medical image analysis is image coregistration which involves information fusion of tomographic diagnostic images obtained from different modalities. We present a novel MRI and PET brain image coregistration technique using binary correlation matching based on multiple image f...

Head movement during a dynamic brain PET/CT imaging results in mismatch between CT and dynamic PET images. It can cause artifacts in CT-based attenuation corrected PET images, thus affecting both the qualitative and quantitative aspects of the dynamic PET images and the derived parametric images. In this study, we developed an automated retrospective image-based movement correction (MC) procedu...

For the problem of image registration based on mutual information ignore global spatial information of the two images, and the lungs PET image is so fuzzy that has fewer correlations with the lungs CT image. This paper proposed a coarse-to-fine image registration method based on region information and mutual information. Experimental results show that this method can effectively to achieve lung...

Positron emission tomography (PET) image reconstruction is challenging for low count frame. The reconstruction is important method to retrieve information that has been lost in the images. To improve image quality, prior information are used. Based on kernel method, PET image intensity in each pixel is obtained from prior information and the coefficients can be estimated by the maximum likeliho...

MRI-PET medical image fusion has important clinical significance. Medical image fusion is the important step after registration, which is an integrative display method of two images. The PET image shows the brain function with a low spatial resolution, MRI image shows the brain tissue anatomy and contains no functional information. Hence, a perfect fused image should contains both functional in...

Spatially registered positron emission tomography (PET), computed tomography (CT), and magnetic resonance (MR) images of the same small animal offer potential advantages over PET alone: CT images should allow accurate, nearly noise-free correction of the PET image data for attenuation; the CT or MR images should permit more certain identification of structures evident in the PET images; and CT ...

INSERM UMR1101, LaTIM, Brest, France Respiratory motion in PET/MR imaging leads to reduced quantitative and qualitative image accuracy. Correction methodologies include the use of respiratory synchronized gated frames which lead to low signal to noise ratio (SNR) given that each frame contains only part of the count available throughout an average PET acquisition. In this work, 4D MRI extracted...

University College London, London, UK Respiratory motion during PET acquisitions can cause image artefacts, with sharpness and tracer quantification adversely affected due to count ‘smearing’. Motion correction by registration of PET gates becomes increasingly difficult with shorter scan times and less counts. The advent of simultaneous PET/MRI scanners allows the use of high spatial resolution...